π-Economy

RAR RUS 7-28 Skvortsova Inga ingavik@mail.ru Teslya Anna antes@list.ru Somov Andrei somovspb@yandex.ru Assessing industrial enterprise readiness for artificial intelligence implementation as a basis for strategic digital transformation directions The relevance of the study is driven by the necessity for industrial enterprises to transition from fragmented experiments with artificial intelligence (AI) to its systemic implementation as a driver of digital transformation. Despite growing investments in Industry 4.0 technologies, a gap persists between ambitions and tangible outcomes. The core problem lies in the absence of a standardized tool for the objective diagnosis of organizational readiness – a company’s ability not only to launch a pilot project but also to ensure the sustainable integration, scaling, and continuous development of AI solutions across the entire value chain. The aim of the research is to bridge this methodological gap by developing, testing, and verifying an Integrated Enterprise AI Readiness Index (AIRI), and to define differentiated strategic trajectories for industrial enterprises with varying levels of digital maturity based on this instrument. Research methods include systems analysis for structuring success factors, comparative analysis for identifying best practices and international trends, as well as the in-depth case study method for empirical validation. The developed index is a weighted integrated model that quantitatively assesses five interrelated components of organizational maturity: data readiness, process maturity, technological architecture, human capital and competencies, and strategy and governance. Validation on five enterprises from different industrial sectors revealed a significant variance in readiness levels and confirmed the tool’s high diagnostic value. Typical “bottlenecks” were identified, such as data fragmentation and competency deficits, which hinder transformation. It has been proven that the key success factor for digital transformation is organizational and process maturity, not merely technological sophistication. The practical significance lies in providing management with a tool for audit, investment prioritization, selection of adequate AI solutions, and realistic forecasting of their return. Research prospects include refining the index's weighting coefficients for various industries, integrating it with strategic management systems, and conducting cross-cultural comparative studies. 10.18721/JE.19201 334.02 artificial intelligence business processes digital transformation predictive analytics industry 4.0 process maturity artificial intelligence readiness index (AIRI) https://economy.spbstu.ru/article/2026.118.1/ 01_skvortsova_teslya_somov.pdf

RAR RUS 29-42 Balog Mikhail Organizational and economic mechanism for ensuring regional economic security in the context of digital transformation Attention to the organizational and economic mechanism for ensuring regional economic security is driven by the need for systemic integration of traditional economic security tools and modern digital technologies into the economy of a constituent entity of the federation. This will create a positive synergistic effect in ensuring the territory’s economic security, impart a holistic and permanently implemented character to this process, and also make it possible to scale this experience to other regions. The aim of this study is to develop an organizational and economic mechanism for ensuring regional economic security, operating within a public-private digital ecosystem. During the study, a comparative analysis of the scientific literature was conducted, which made it possible to form a resource-terminological base for this organizational and economic mechanism. According to the developed definition, the organizational and economic mechanism for ensuring regional economic security is a set of strategic, economic, informational, organizational, legal, institutional, and other instruments, provided with the necessary resources and united by cause-and-effect and functional relationships, performing their functions in the physical and digital dimensions, and organized within a public-private digital ecosystem that ensures the harmonized implementation of state, corporate, and public interests, resulting in the creation of value propositions for all participants in the mechanism. A distinctive feature of the proposed definition of the organizational and economic mechanism for ensuring the economic security of a region is the substantiation of its functioning based on a public-private digital ecosystem, which improves the quality of information processing and the operational, tactical, and strategic management decisions made on its basis, monitors the effectiveness and quality of these decisions’ implementation, and reduces the response time for neutralizing challenges and threats to the region’s economic security. This paper presents graphical modeling of the organizational and economic mechanism for ensuring the region’s economic security. The proposed model incorporates principles and participants, including governing bodies, objects, functions, resources, tools, value propositions and effects, as well as digital technologies integrated into the public-private digital ecosystem. The positive effects of involvement in the ecosystem for corporate participants (search for counterparties, additional utilization of production capacities, project management, optimization of business processes, cost reduction) will enable the monetization of the organizational and economic mechanism. 10.18721/JE.19202 332.1 economic mechanism organizational and economic mechanism economic security digital transformation regional economy digital ecosystem monetization https://economy.spbstu.ru/article/2026.118.2/ 02_balog.pdf

RAR RUS 43-64 Muljono Wiryanta wiryantamuljono@gmail.com Setiyawati Sri Setiawati Pertiwi Priyanka Setyanto Padmanabha Adyaksa Geopolitical trade-off: Exchange rate anchor vs structural vulnerability in emerging Asia’s core inflation This study explores the conflict between domestic structural reforms (structural anchors) and the external financial framework (currency dependence) and their impact on monetary policy resilience in Emerging Southeast Asia (ESEA). It connects macroeconomic evidence with the geopolitical economy. To ensure analytical clarity, these anchors are conceptually defined by factors such as institutional quality, trade diversification and the extent of domestic price rigidity. Amidst the growing fragmentation of global geopolitics and the enduring dominance of the US dollar, ESEA nations face a significant dilemma. This dilemma encapsulates a fundamental geopolitical trade-off: should they prioritize the strengthening of their internal economies and institutions, or should they risk becoming constrained by policies shaped by global financial shocks? To address this issue, we utilize a Structural Vector Autoregression (SVAR) model to analyze the dynamics of core inflation in two contrasting cases: Indonesia, which employs Rupiah flexibility, and Vietnam, which maintains a Managed Dong anchor. Our analysis covers the period from the first quarter of 2015 to the fourth quarter of 2024, allowing for an empirical comparison of the effectiveness of their respective policy models. Our analysis indicates that Indonesia's inflation volatility is predominantly influenced by global shocks and a high Exchange Rate Pass-Through (ERPT), highlighting the significant costs associated with currency dependence. In contrast, Vietnam maintains relative price stability through its managed exchange rate, which serves as an effective, state-directed structural shield. The findings suggest that the struggle for monetary autonomy is materially quantified by the degree of ERPT and the choice of exchange rate regime. Crucially, this stability is achieved at the potential cost of diminished monetary policy signaling and the necessity for larger external reserve buffers. This study, therefore, offers crucial, empirically backed insights into the restricted policy space available to ESEA nations amidst global financial volatilitye. 10.18721/JE.19203 658.5 core-inflation structural VAR exchange rate pass-through global-shocks Emerging Southeast Asia geopolitical trade-off Indonesia Vietnam https://economy.spbstu.ru/article/2026.118.3/ 03_mulono_setiyavati_setiavati_setyanto.pdf

RAR RUS 67-87 Beilin Igor Khomenko. Vadim Spatial and economic integration of the innovative and industrial potential of oil and gas regions to improve their economic security The development of effective economic security systems for oil and gas regions in the context of sanctions impacting the Russian economy, a significant portion of whose revenue comes from oil and gas exports, is possible through the territorial and intersectoral adaptation of regional innovative industrial complexes to address the common challenges of developing high-tech, import-substituting methods for extracting and processing hard-to-recover hydrocarbon resources. The objective of this study is to develop innovative industrial criteria for the economic security of oil and gas regions and rational options for their spatial and economic integration within the Volga-Ural oil and gas province, relevant given changing national institutional settings and macroeconomic indicators. To achieve this goal, the following objectives were set and addressed: an economic and theoretical review of neo-industrialization pathways in the new Russian context of spatial economic interactions and the institutional framework for integrated subsoil development using regional innovative industrial infrastructures in the context of an accelerated transition to national technological sovereignty; an economic and theoretical review of the organizational, managerial, investment, and financial barriers to the economic security of oil and gas regions, threats to their economic security in the focus of Russia’s anti-sanction geostrategic policy, and the adaptation of the country’s spatial and economic structure to the mechanisms of its imbalance and the emergence of crises; a regression and structural analysis of the volume of shipped goods of domestic production, completed work, and services in the extractive and manufacturing industries of the oil and gas regions of the Volga Federal District, as well as a structural analysis of the profitability of their organizations' assets and products; an interregional dispersion and cluster analysis of the developed innovative and industrial criteria for the economic security of the oil and gas regions of the Volga Federal District. As a result of the developed approach, two interregional innovative and industrial clusters were formed in the extractive and manufacturing industries, increasing the level of economic security of the oil and gas regions of the Volga Federal District. In the extractive industry, such clusters are feasible between the Republic of Bashkortostan, the Udmurt Republic, and Samara Oblast, on the one hand, and Perm Krai and Orenburg Oblast, on the other. In the manufacturing industry, innovative industrial integration is feasible between the Udmurt Republic and Samara Oblast, on the one hand, and the Republic of Bashkortostan, Perm Krai, and Orenburg Oblast, on the other. 10.18721/JE.19204 332.1 economic security oil and gas region regional economy industrial economy innovation economy environmental economics https://economy.spbstu.ru/article/2026.118.4/ 04_beilin_homenko.pdf

RAR RUS 85-105 Nikolaev Mikhail fef-sp.ucoz.ru Makhotaeva Marina makhotaeva@mail.ru Assessment and justification of directions for improving the efficiency of regional scientific, technological and innovation policy 10.18721/JE.19205 332.1 scientific technological and innovation policy manufacturing regional potential technological innovation technological sovereignty https://economy.spbstu.ru/article/2026.118.5/ 05_nikolaev_mahotaeva.pdf

RAR RUS 106-127 Nizhegorodov Anatoly Kurnikova Marina Balanced development of the macroregion’s manufacturing industry under new industrialization (a case study of the Volga Federal District) In the context of geopolitical challenges and the need for Russia's technological sovereignty, the key imperative is new industrialization, which involves a qualitative transition to digital and intellectual production. However, the policy of concentrating resources in historically established industrial centers deepens interregional disparities. This study aims to address the contradiction between the effectiveness of concentration and the need for balanced development, using the Volga Federal District (VFD) as a case study. The goal is to develop and test a concept for the balanced development of the manufacturing industry based on the transition from a “catch-up” development model to a strategy of differentiated integration of regions with different potential into unified production and cooperation chains. The methodology includes three stages. At the first stage, a comprehensive assessment of the potential for new industrialization was conducted based on four blocks (industrial, human resources, investment, and innovation) using data from Rosstat for 2023. The integral index allowed for the identification of leading regions, regions with average potential, and regions with low potential. At the second stage, a “potential–dynamics” matrix was constructed, classifying regions into four groups (Leaders, Catch-up Development Regions, Stable Regions, and Problem Regions) and identifying strategic priorities. At the third stage, functional models of interregional value creation chains were designed for the key clusters of the VFD: the automotive industry, aircraft manufacturing, petrochemicals, and agro-industry. The results revealed pronounced polarization: the two leading regions account for 32% of the gross regional product (GRP) of manufacturing industry and 46% of investments, while labor productivity is twice the average. At the same time, a number of regions with low absolute potential demonstrate high growth rates, making them potential growth points within cooperation networks. The key conclusion is the need to transition from a policy of fiscal equalization to a strategy of specialized integration of lagging regions as component suppliers into the clusters of leading regions. The practical significance lies in the creation of diagnostic tools and functional cooperation schemes to transform spatial heterogeneity into a growth factor for the technological sovereignty of the macroregion. 10.18721/JE.19206 332.13 new industrialization manufacturing industry balanced regional development pro-duction and cooperation chains https://economy.spbstu.ru/article/2026.118.6/ 06_nizhegorodov_kurnikova.pdf

RAR RUS 128-143 Alekseeva Arina Potsulin Anton anton.potsulin@yandex.ru Arbildo Prieto Diego Héctor Alonso Factors of using generative artificial intelligence in the design of educational products The relevance of the research is due to the rapid development of generative artificial intelligence (GenAI), which opens up new opportunities for designing educational products, as well as the growth of institutional and financial investments of educational organizations in AI technologies, the effectiveness of which is largely determined by factors of professional acceptance. Despite GenAI’s high technological potential, there remains a significant gap between its capabilities and actual integration into educational design processes, which creates managerial and economic risks of inefficient use of digital innovations. The aim of the work is to identify and analyze the key factors determining the introduction of GenAI technologies into educational design processes in higher education institutions from the standpoint of the theory of technology adoption and digital transformation management. The methodological basis of the study was the extended model of the Unified Theory of Acceptance and Use of Technology (UTAUT), supplemented by the author’ construct “Intellectual Trust”. The empirical verification of the hypotheses was carried out using a quantitative survey of 54 specialists from Russia and Latin American countries and Partial Least Squares Structural Equation Modeling (PLS-SEM). It was found that perceived ease of use (β = = 0.310; p < 0.05) and intellectual trust (β = 0.348; p < 0.05) are key determinants of behavioral intent and jointly explain 30.6% of its variance, while the expected usefulness and intention of use have a significant impact on the actual use of GenAI; the model explains 47.8% of the variance of use. The scientific novelty lies in the empirical validation of intellectual trust as a critical factor in the adoption of GenAI and the identification of the absence of direct influence of social and technical and organizational factors of the UTAUT in this professional context. The practical significance of the research is to substantiate managerial approaches to the integration of GenAI, focused on proving the professional usefulness of technology and building trust in algorithmic solutions. 10.18721/JE.19207 330.34 generative artificial intelligence educational product design technology adoption unified theory of technology adoption and use structural equation method https://economy.spbstu.ru/article/2026.118.7/ 07_alekseeva_potsulin_arbildo_prieto_d_.pdf

RAR RUS 144-160 Erastov Dmitry Anisimov Aleksandr Evolution of public-private partnership models in industry: from infrastructure projects to technological and competence partnerships The article explores the fundamental transformation of the public-private partnership (PPP) architecture in the industrial sector as a response to the challenges of technological sovereignty and global competition. The relevance of the work is due to the critical need to rethink traditional, mainly infrastructural PPP models in the face of sanctions pressure, disruption of global value chains and the strategic transition of the national economy to a knowledge-based model and the generation of its own innovations. The aim of the study is to identify and substantiate the trajectory of the evolution of PPP architecture in industry from infrastructure projects to technological and competence-based partnerships. To achieve this goal, the following tasks were consistently solved: a critical analysis of theoretical approaches to defining the architecture of PPPs in the context of evolutionary economic theory and the concept of dynamic capabilities was carried out; based on a comparative analysis and risk structure, key parameters characterizing different generations of partnerships (PPPs 1.0, 2.0, 3.0) were systematized; based on empirical data and a case study of Russian projects (FRP, PIS, end- to-end technology consortia), a conceptual three-level model of a third-generation PPP has been developed and visualized. The research methods include dialectical, institutional and comparative analysis, as well as case studies of real projects. The research resulted in systematization of three generations of PPP architecture (infrastructural – PPP 1.0, modernization – PPP 2.0, competence – PPP 3.0), identification of key drivers of evolution and development of a three-level model PPP 3.0. The results obtained concretize the paradigm shift from asset management to knowledge creation management, where intangible competencies become the key result. The model details the interaction of the technological core, the competence infrastructure and the institutional framework, revealing the mechanism of synergy between them. The scientific novelty lies in presenting evolution as a qualitative paradigm shift and in substantiating the concept of “partnerships of competencies” as a networked, learning ecosystem. The practical significance is determined by the possibility of applying the proposed model to form state industrial policy and enterprise development strategies aimed at strengthening competitiveness through the creation of intangible assets and technological competencies. 10.18721/JE.19208 330.3+334+338.45 public-private partnership PPP architecture industrial policy technological sovereignty competencies innovation ecosystem development institutions dynamic abilities risk management intangible assets https://economy.spbstu.ru/article/2026.118.8/ 08_erasatov_anisimov.pdf

RAR RUS 161-176 Krasyuk Tatyana actualbil@gmail.com Company value management based on graph stochastic modeling The volatility of the external economic environment actualizes the transition from deterministic economic and financial models to models with dynamic and stochastic properties. The purpose of the study is to improve the quality of management decisions in the field of company value management through the development and application of a graph stochastic model that ensures the adaptation of corporate governance to conditions of high volatility and uncertainty. Objectives of the study are as follows: to conduct a bibliographic analysis of the theory and practice of using Bayesian graph networks in the Russian economy; to develop an enlarged graph dynamic model of the formation of the value of a firm as a target indicator of corporate governance; on the basis of empirical data of a public company in the consumer sector to determine the stable structure and relationships of financial and economic indicators that form the value of the company; to test an enlarged graph stochastic model on empirical data; to calculate the aggregate distribution of the company’s value taking into account a set of influencing factors; to calculate the risks of positive and negative scenarios with a confidence level of the interval. An analysis of consumer sector company data for seven years was conducted, an enlarged graph dynamic model of value formation was developed, the parameters of the distribution of the values of the factors – nodes of the model were set. The data were simulated using the Monte Carlo method, the target value indicator was calculated in a probabilistic representation, the risks of positive and negative outcomes were assessed, scatter plots of influencing factors and the result were presented. To calculate and visualize the modeling results, a platform for stochastic modeling and interpretable AI based on Bayesian networks was used. Scientific novelty of the study is the use of Bayesian graph networks for cost engineering and upside risk assessment for the purposes of adaptive corporate governance, modeling of value in a probabilistic representation and with the calculation of an aggregate distribution based on empirical data of a consumer sector company, approbation of the approach of causal stochastic modeling to assess the probabilistic nature of the impact of shocks with a positive outcome on the cost, obtaining more realistic results in comparison with the static deterministic approach. Prospects for further research are the integration of the stochastic modeling approach into the practice of target engineering, the decomposition of factors – nodes of graph models, the development of cost models with an assessment of the influence of idiosyncratic factors in various industries. 10.18721/JE.19209 338.984, 338.27, 336.648 corporate governance adaptive management methods economic model risk modeling opportunity in risk modeling upside risk graph model stochastic modeling cost assessment Monte-Carlo method https://economy.spbstu.ru/article/2026.118.9/ 09_krasyuk.pdf

RAR RUS 177-192 Stepanova Ksenia Kudryavtseva Tatiana tankud28@mail.ru A model for managing the digitalization efficiency of the production process in light industry enterprises In Russia, the federal project “Efficient and Competitive Economy” is being implemented, aimed at increasing enterprise labor productivity. One of the ways to improve productivity is the digitalization of production processes. The use of digital technologies together with lean manufacturing methods and tools can improve the efficiency of implemented solutions, leading to significant increase in enterprise productivity. A problem arises, which consists in the absence of models, indicators, and their criterion values, reflecting the effectiveness of managerial decisions regarding the digitalization of production processes when implementing lean manufacturing tools and methods. Russia’s light industry faces a number of challenges that contribute to its lagging behind global industry leaders. One such challenge is high production labor intensity and low labor productivity. The growth of the latter will be ensured by the introduction of lean production tools together with digital technologies. Accordingly, the aim of this study is to develop a model for managing the efficiency of digitalization of production processes at light industry enterprises, taking into account industry-specific and regional features. This study presents the author’s approach to assessing the efficiency of digitalization of production processes at light industry enterprises. This approach takes into account integral efficiency, including economic, social, production, technological, and managerial efficiencies. The study also presents a model for managing the efficiency of digitalization of production processes of light industry enterprises, taking into account the industry-specific indicators of leading regions; as well as the approbation of the presented approach and model. The study identified leading regions in light industry, including the Ivanovo, Rostov, and Ryazan oblasts. The model for managing the efficiency of digitalization of production processes of light industry enterprises was tested at a sewing enterprise that implemented RFID technology in production together with lean manufacturing tools and methods. The model’s approbation demonstrated the economic efficiency of the considered production digitalization project, and its integral efficiency indicator than the industry indicators in leading regions. 10.18721/JE.19210 338.012 management model digitalization of the production process light industry efficiency https://economy.spbstu.ru/article/2026.118.10/ 10_stepanova_kudryavtseva.pdf